Development of a Computer-aided Polypectomy Decision Support

Adenomatous Polyps Clinical Trial

Official title:

Development of a Computer-aided Polypectomy Decision Support

Clinical Trial Details — Status: Withdrawn

Administrative data

• NCT number: NCT04811937
• Other study ID #: 20.382
• Status: Withdrawn
• Phase: N/A
• Start date: December 2021
• Est. completion date: April 2023

Study information

• Verified date: December 2022
• Source: Centre hospitalier de l'Université de Montréal (CHUM)
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Quality components of colonoscopy include the detection and complete removal of colorectal polyps, which are precursors to CRC. However, endoscopic ablation may be incomplete, posing a risk for the development of "interval cancers". The investigators propose to develop a solution based on artificial intelligence (AI) (CADp computer-aided decision support polypectomy) to solve this problem.This research project aims to develop CADp, a computer decision support solution (CDS) for the ablation of colorectal polyps from 1 to 20 mm.

Description:

This research project aims to develop CADp, a computer-based decision support (CDS) solution for the removal of colorectal polyps ranging from 1-20 mm. The investigators will use a video and image dataset of polypectomy procedures to train the CADp model; thus, it can provide real-time overlaid video feedback for polypectomy procedures based on five specific metrics: 1) estimation of polyp size; 2) prediction of morphology and histology; 3) suggestion of an appropriate resection accessory and technical approach based on the characteristics, size, and histology of the polyp according to current guidelines; 4) image overlay, based on semantic image segmentation technology, showing the extent of the lesion and suggestion of an appropriate resection margin contour around the polyp to ensure its complete removal; 5) post-resection analysis to identify any remnant polyp tissue or insufficient resection margin that may increase this risk.

The investigators will collect a set of images and video data from live polypectomy procedures to leverage recent advances in AI technology to train deep learning models. This dataset will be obtained prospectively from a cohort of adults (ages 45-80) undergoing screening, diagnostic, or surveillance colonoscopies. To train the CADp solution, the investigators will obtain the corresponding completeness of resection status using the yield of post-resection margin biopsies. The dataset will be divided into two groups, the training, and the CADp test, respectively.

Recruitment information / eligibility

• Status: Withdrawn
• Enrollment: 0
• Est. completion date: April 2023
• Est. primary completion date: April 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 45 Years to 80 Years

Eligibility

Inclusion Criteria:

• Signed informed consent

• Age 45-80 years

• Indication to undergo a lower GI endoscopy.

Exclusion Criteria:

• Known inflammatory bowel disease

• Active colitis

• Coagulopathy

• Familial polyposis syndrome;

• Poor general health, defined as an American Society of Anesthesiologists (ASA) physical status class >3

• Emergency colonoscopies

Related Conditions & MeSH terms

• Adenomatous Polyps

Intervention

Diagnostic Test:
• Computer-aided polypectomy decision support by Artificial Intelligence
The AI system will capture the live video of the procedure and the AI feedbackwill be shown on a second screen installed next to the regular endoscopy screen. Screen A will show the regular endoscopy image and screen B will show the regular endoscopy image together with the areas that might harbor a polyp and the information to help the polypectomy.

Locations

Country	Name	City	State
Canada	Centre Hospitalier Universitaire de Montréal	Montréal	Quebec

Sponsors (1)

Lead Sponsor	Collaborator
Centre hospitalier de l'Université de Montréal (CHUM)

Country where clinical trial is conducted

Canada, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Accuracy of the CADp system	accuracy with which the CADp system predicts completeness of polypectomy in the test set with the reference standard for completeness being determined by the histology of post-polypectomy margin biopsies; if free from any polyp tissue (adenomatous, serrated or hyperplastic), the resection will be considered complete. If remnant polyp tissue is detected in any one or more of the margin biopsies the resection is deemed incomplete	3 weeks
Primary	Completeness of polypectomy	We will evaluate the agreement between the different subjective and objective ways of assessing the completeness of the polypectomy : evaluation of margins (presence or not, measurement of margins) by endoscopists self-assessment, and by expert consensus.	1 month
Primary	Training CADp	Evaluation of the concordance of data on polyp size, extension of margins around the polyp, quality of resection between clinical data (endoscopists' self-assessment and experts' assessments) and CADp prediction.	1 month
Primary	Validity of the choice of primary outcome	Based on the results and comparison of the different assessment methods, we will perform sensitivity analyses to assess the validity and robustness of the choice of primary outcome.	1 month